Now showing items 551-570 of 775

    • Programming a Sensor Network as an Amorphous Medium 

      Bachrach, Jonathan; Beal, Jacob (2006-06)
      In many sensor network applications, the network is deployedto approximate a physical space. The network itself is not ofinterest: rather, we are interested in measuring the propertiesof the space it fills, and of establishing ...
    • Programming an Amorphous Computational Medium 

      Beal, Jacob (2004-09)
      Amorphous computing considers the problem of controllingmillions of spatially distributed unreliable devices which communicateonly with nearby neighbors. To program such a system, we need a highleveldescription language ...
    • Programming Manifolds 

      Bachrach, Jonathan; Beal, Jacob (2007)
      Many programming domains involve the manipulation of values distributed through a manifold - examples include sensor networks, smart materials, and biofilms. This paper describes a programming semantics for manifolds based ...
    • A Projected Subgradient Method for Scalable Multi-Task Learning 

      Quattoni, Ariadna; Carreras, Xavier; Collins, Michael; Darrell, Trevor (2008-07-23)
      Recent approaches to multi-task learning have investigated the use of a variety of matrix norm regularization schemes for promoting feature sharing across tasks.In essence, these approaches aim at extending the l1 framework ...
    • Propagation Networks: A Flexible and Expressive Substrate for Computation 

      Radul, Alexey (2009-11-03)
      I propose a shift in the foundations of computation. Practically all ideas of general-purpose computation today are founded either on execution of sequences of atomic instructions, i.e., assembly languages, or on evaluation ...
    • Prophet: Automatic Patch Generation via Learning from Successful Human Patches 

      Long, Fan; Rinard, Martin (2015-05-26)
      We present Prophet, a novel patch generation system that learns a probabilistic model over candidate patches from a large code database that contains many past successful human patches. It defines the probabilistic model ...
    • Prophet: Automatic Patch Generation via Learning from Successful Patches 

      Long, Fan; Rinard, Martin (2015-07-13)
      We present Prophet, a novel patch generation system that learns a probabilistic model over candidate patches from a database of past successful patches. Prophet defines the probabilistic model as the combination of a ...
    • Propositional and Activity Monitoring Using Qualitative Spatial Reasoning 

      Lane, Spencer Dale (2016-12-14)
      Communication is the key to effective teamwork regardless of whether the team members are humans or machines. Much of the communication that makes human teams so effective is non-verbal; they are able to recognize the ...
    • Proving Atomicity: An Assertional Approach 

      Chockler, Gregory; Lynch, Nancy; Mitra, Sayan; Tauber, Joshua (2005-07-22)
      Atomicity (or linearizability) is a commonly used consistency criterion for distributed services and objects. Although atomic object implementations are abundant, proving that algorithms achieve atomicity has turned out ...
    • A Publish-Subscribe Implementation of Network Management 

      Simosa, Jorge D. (2013-06-04)
      As modern networks become highly integrated, heterogeneous, and experience exponential growth, the task of network management becomes increasingly unmanageable for network administrators and designers. The Knowledge Plane ...
    • Pyramid Match Kernels: Discriminative Classification with Sets of Image Features 

      Grauman, Kristen; Darrell, Trevor (2005-03-17)
      Discriminative learning is challenging when examples are setsof local image features, and the sets vary in cardinality and lackany sort of meaningful ordering. Kernel-based classificationmethods can learn complex decision ...
    • Pyramid Match Kernels: Discriminative Classification with Sets of Image Features (version 2) 

      Grauman, Kristen; Darrell, Trevor (2006-03-18)
      Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernel-based classification methods can learn complex decision boundaries, ...
    • Quantifier-Free Boolean Algebra with Presburger Arithmetic is NP-Complete 

      Kuncak, Viktor (2007-01-01)
      Boolean Algebra with Presburger Arithmetic (BAPA) combines1) Boolean algebras of sets of uninterpreted elements (BA)and 2) Presburger arithmetic operations (PA). BAPA canexpress the relationship between integer variables ...
    • Quantitative Information Flow as Network Flow Capacity 

      McCamant, Stephen; Ernst, Michael D. (2007-12-10)
      We present a new technique for determining how much information abouta program's secret inputs is revealed by its public outputs. Incontrast to previous techniques based on reachability from secretinputs (tainting), it ...
    • Quantitative Information-Flow Tracking for C and Related Languages 

      McCamant, Stephen; Ernst, Michael D. (2006-11-17)
      We present a new approach for tracking programs' use of data througharbitrary calculations, to determine how much information about secretinputs is revealed by public outputs. Using a fine-grained dynamicbit-tracking ...
    • Quaternionic Representation of the Riesz Pyramid for Video Magnification 

      Wadhwa, Neal; Rubinstein, Michael; Durand, Fredo; Freeman, William T. (2014-04-26)
      Recently, we presented a new image pyramid, called the Riesz pyramid, that uses the Riesz transform to manipulate the phase in non-oriented sub-bands of an image sequence to produce real-time motion-magnified videos. In ...
    • Queueing Theory Analysis of Labor & Delivery at a Tertiary Care Center 

      Gombolay, Matthew; Golen, Toni; Shah, Neel; Shah, Julie (MIT CSAIL, 2014-12-16)
      Labor and Delivery is a complex clinical service requiring the support of highly trained healthcare professionals from Obstetrics, Anesthesiology, and Neonatology and the access to a finite set of valuable resources. In ...
    • RamboNodes for the Metropolitan Ad Hoc Network 

      Beal, Jacob; Gilbert, Seth (2003-12-17)
      We present an algorithm to store data robustly in a large, geographically distributed network by means of localized regions of data storage that move in response to changing conditions. For example, data might migrate away ...
    • Random Lens Imaging 

      Fergus, Rob; Torralba, Antonio; Freeman, William T. (2006-09-02)
      We call a random lens one for which the function relating the input light ray to the output sensor location is pseudo-random. Imaging systems with random lensescan expand the space of possible camera designs, allowing new ...
    • Random-World Semantics and Syntactic Independence for Expressive Languages 

      McAllester, David; Milch, Brian; Goodman, Noah D. (2008-05-03)
      We consider three desiderata for a language combining logic and probability: logical expressivity, random-world semantics, and the existence of a useful syntactic condition for probabilistic independence. Achieving these ...